Marco Grimaldi

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The vast amount of music available electronically presents considerable challenges for information retrieval. There is a need to annotate music items with descriptors in order to facilitate retrieval. In this paper we present a process for determining the music genre of an item using a new set of descriptors. A Wavelet Packet Transform is applied to obtain(More)
Automatic annotation of music files is a key problem in multimedia information retrieval. In this paper we present a solution to this problem that addresses the issues of feature extraction, feature selection and design of classi-fier. We outline a process for feature extraction based on the discrete wavelet packet transform and we evaluate a variety of(More)
The vast amount of music available electronically presents considerable challenges for information retrieval. There is a need to annotate music items with descriptors in order to facilitate retrieval. In this paper we present a process for determining the music genre of an item using the Discrete Wavelet Transform and a round-robin classification technique.(More)
This paper describes the operation of and research behind a networked application for the delivery of personalised streams of music at Trinity College Dublin. Smart Radio is a web based client-server application that uses streaming audio technology and recommendation techniques to allow users build, manage and share music programmes. While it is generally(More)
In recent years many research projects have been published in the area of multimedia information retrieval (MIR). The requirement is to enable access to multimedia data with the same ease as textual information. A distinctly new branch in the MIR research area is categorizing music items by user preference. Some experiments proposed and published by(More)
The vast amount of music available electronically presents considerable challenges for information retrieval. There is a need to annotate music items with descriptors in order to facilitate retrieval. In this paper we present a process for determining the music genre of an item using the Discrete Wavelet Transform and a round-robin classification technique.(More)
Speaker verification is a challenging problem in speaker recognition where the objective is to determine whether a segment of speech in fact comes from a specific individual. In supervised machine learning terms this is a challenging problem as, while examples belonging to the target class are easy to gather, the set of counterexamples is completely open.(More)
RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently. The overall network is obtained by joining all the neighborhoods. RegnANN makes no assumptions about the nature of the relationships between(More)